N-bir: Reducción del tiempo del ensayo de burn-in de convertidores electrónicos de potencia mediante optimización numérica

• IÑAKI MARTINEZ GARRIZ ^[1] ; PILAR HERRERA PLAZA ^[1] ; MAIALEN LARRETXEA URRUTIA ^[2]
  1. [1] Asociación Industria Navarra
  2. [2] INGETEAM POWER TECHNOLOGY
• Localización: Revista DYNA, ISSN-e 0012-7361, ISSN 0012-7361, Vol. 99, Nº 2, 2024, págs. 201-207
• Idioma: español
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• Resumen

  • Burn-in testing is an effective method for detecting early faults in electronic products before they reach the market. This test has a high cost due to lengthy test time on a test bench. In this paper, we propose N-BIR (Numeric optimization approach for power electronic Burn-In testing time Reduction), an algorithm capable of predicting the burn-in test temperature of power electronic converters, intending to shorten the duration of such tests. This algorithm optimizes by least squares a theoretical model of the system, using as data a fraction of the total burn-in test. Moreover, not only is it capable of making accurate predictions, but it also accompanies them with a prediction interval, so that the algorithm itself can quantify how confident it is of its predictions. We show that using 40% of a conventional rolling test total, the proposed algorithm outperforms several of today's most common Machine Learning algorithms. Furthermore, we show that it can reduce burning time by 50% to 60% by making accurate predictions, which makes it possible to identify a significant portion of converters that don't require full testing, ultimately lowering costs and boosting productivity.